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Panel Data Specifications in Nonparametric Kernel Regression: An Application to Production Functions

Author

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  • Tomasz Czekaj

    (Department of Food and Resource Economics, University of Copenhagen)

  • Arne Henningsen

    (Department of Food and Resource Economics, University of Copenhagen)

Abstract

We discuss nonparametric regression models for panel data. A fully nonparametric panel data specification that uses the time variable and the individual identifier as additional (categorical) explanatory variables is considered to be the most suitable. We use this estimator and conventional parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we found the estimates of the fully nonparametric panel data model to be more reliable.

Suggested Citation

  • Tomasz Czekaj & Arne Henningsen, 2013. "Panel Data Specifications in Nonparametric Kernel Regression: An Application to Production Functions," IFRO Working Paper 2013/5, University of Copenhagen, Department of Food and Resource Economics.
    • Handle: RePEc:foi:wpaper:2013_5
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    References listed on IDEAS

    as
    1. Tomasz Gerard Czekaj & Arne Henningsen, 2012. "Comparing Parametric and Nonparametric Regression Methods for Panel Data: the Optimal Size of Polish Crop Farms," IFRO Working Paper 2012/12, University of Copenhagen, Department of Food and Resource Economics.
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    Cited by:

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    2. Changwoo Nam & Jiyoon Oh, . "Changes in Competition of Small vs. Large Firms from International Trade," Chapters, in: Chin Hee Hahn & Dionisius A. Narjoko (ed.), Globalization and Performance of Small and Large Firms, chapter 5, pages V-1 - V-4, Economic Research Institute for ASEAN and East Asia (ERIA).
    3. Titl, Vitezslav & De Witte, Kristof & Geys, Benny, 2021. "Political donations, public procurement and government efficiency," World Development, Elsevier, vol. 148(C).
    4. Czekaj, Tomasz G., 2015. "Measuring the Technical Efficiency of Farms Producing Environmental Output: Semiparametric Estimation of Multi-output Stochastic Ray Production Frontiers," 2015 Conference, August 9-14, 2015, Milan, Italy 211555, International Association of Agricultural Economists.
    5. Tomasz Gerard Czekaj & Arne Henningsen, 2013. "Panel Data Nonparametric Estimation of Production Risk and Risk Preferences: An Application to Polish Dairy Farms," IFRO Working Paper 2013/6, University of Copenhagen, Department of Food and Resource Economics.
    6. G. Ardizzi & F. Crudu & C. Petraglia, 2015. "The Impact of Electronic Payments on Bank Cost Efficiency: Nonparametric Evidence," Working Paper CRENoS 201517, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    7. Jha, Amit Prakash & Mahajan, Aarushi & Singh, Sanjay Kumar & Kumar, Piyush, 2022. "Renewable energy proliferation for sustainable development: Role of cross-border electricity trade," Renewable Energy, Elsevier, vol. 201(P1), pages 1189-1199.
    8. Tomasz Gerard Czekaj, 2013. "Measuring the Technical Efficiency of Farms Producing Environmental Output: Parametric and Semiparametric Estimation of Multi-output Stochastic Ray Production Frontiers," IFRO Working Paper 2013/21, University of Copenhagen, Department of Food and Resource Economics.
    9. Durga P. Gautam, 2014. "Remittances and Governance: Does the Government Free Ride?," Working Papers 14-40, Department of Economics, West Virginia University.
    10. Geraldine Henningsen & Arne Henningsen & Christian Henning, 2015. "Transaction costs and social networks in productivity measurement," Empirical Economics, Springer, vol. 48(1), pages 493-515, February.

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    More about this item

    Keywords

    nonparametric kernel regression; panel data; choice of the kernel; kernels for categorical variables; production function;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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